The short answer is that I don’t know because the BAAJA studies by think tanks that I’m aware of do not, as far as I can tell, disclose their full modeling details or make their code open source. However, I surmise that the other studies assume that energy demand is the same with and without BAAJA.

I don’t think this assumption is plausible. While some of the probabilistic scenarios that I run do include zero electricity demand growth, most include demand growth for both electricity and domestic fossil fuel direct use.

I assume that if BAAJA accelerates buildout of electricity and natural gas infrastructure, then it alleviates transmission and resource-adequacy constraints, for both electricity and natural gas, that might otherwise slow or prevent demand growth from, for example, data centers or other large loads. BAAJA’s supply-side interventions could also increase energy demand indirectly through price effects.

If domestic fossil fuel demand grows, then climate and mortality impacts from domestic fossil fuel demand grow. If electricity demand grows and is not met by 100% clean electricity generation, then fossil fuel electricity generation grows and so do climate and mortality impacts.

I model BAAJA as likely increasing electricity demand. In most of the probabilistic scenarios that I run, clean electricity growth meets only a portion of demand growth. Fossil fuel electricity growth meets the rest of demand growth, increasing emissions.

BAAJA could increase electricity demand by accelerating buildout of power lines or accelerating processing of generation interconnection queues, alleviating transmission or resource-adequacy constraints that could otherwise slow interconnection of data centers or other large loads to transmission grids. Alternatively or additionally, BAAJA could increase behind-the-meter electricity demand at data centers by accelerating buildout of natural gas pipelines or production, alleviating analogous transmission or resource-adequacy constraints that could otherwise slow interconnection of data centers to the natural gas pipelines that supply behind-the-meter turbines.

I use “2025 as it was” as a baseline, rather than looking ahead over the coming decades, for two reasons. First, defining a forward-looking baseline requires making subjective modeling choices about future prices of electrical energy and capacity, future electricity and fossil fuel demand, future constraints in electricity and pipeline networks, discount rates, and other uncertain parameters. Using a retrospective baseline reduces uncertainty and subjectivity by removing dependence on these modeling choices.

Second, in the field of sequential decision-making under uncertainty, where much of my research focuses, understanding realistic near-term consequences is generally more important than exploring far-future possibilities. This suggests that to support good decision-making today, it is more important to characterize BAAJA’s potential impacts this decade, when United States energy systems are unlikely to diverge substantially from their 2025 state, than to speculate about energy systems in 2040.

I don’t model BAAJA’s potential impacts on residential electricity bills. However, other BAAJA modeling studies have estimated bill savings on the order of $15 to $70 per household per year, or 0.8% to 3.8%. (From the Residential Energy Consumption Survey, the average household electricity bill in 2020 was $1,380. Inflation-adjusting to 2025 dollars and adding 7.5% to reflect recent increases in (inflation-adjusted) residential electricity prices gives an estimated annual bill of a bit over $1,800.)

However, as far as I can tell from the incomplete information these studies disclose about their modeling, they assume that electricity demand is the same with and without BAAJA. Under this assumption, BAAJA should indeed reduce electricity prices, as it would increase supply, relative to the assumed baseline, while demand remained constant. However, if BAAJA potentially increases both electricity demand and supply—a possibility I consider—then price reductions may be smaller or nonexistent.

I would have loved to submit this study for peer review in a reputable academic journal. Unfortunately, there are only 40 days between the September 30 publication of the draft bill text and the likely Senate vote on November 9. In 16 years of publishing scientific papers, I’ve never seen peer review turn around that quickly. That said, I’ve tried to follow good practices by clearly explaining the model and making the code open source. I will do my best to respond to constructive feedback.